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It is emphasized that the shocks in structural vector autoregressions are only identified up to sign and it is pointed out that this feature can result in very misleading confidence intervals for impulse responses if simulation methods such as Bayesian or bootstrap methods are used. The confidence intervals heavily depend on which variable is used for fixing the sign of the initial responses. In particular, when the shocks are identified via long-run restrictions the problem can be severe. It is pointed out that a suitable choice of variable for fixing the sign of the initial responses can result in substantial reductions in the confidence bands for impulse responses.

This paper investigates the interdependence of stock returns with some other financial variables applied to several European Telecommunications institutions. In particular, using a multivariate vector autoregressive (VAR) approach this study examines the relation, the direction of the relation, as well as the effects among stock returns, index returns, earnings, capital expenditures and interest rate for companies that play major role in their home stock markets. Unlike the fact that many other previous studies have indicated clear findings of the direction of the causality between those variables, this research cannot support a uniform behavior, although, the selected telecommunications companies have many common characteristics.

Mestrado em Econometria Aplicada e Previsão O comportamento dos preços do porco no produtor em Portugal são influenciados pela trajectória dos preços do porco em Espanha, sendo que os produtores no mercado português são price-takers face ao mercado espanhol. Tal deve-se à proximidade entre ambos os países, ao facto de Espanha ser o principal parceiro comercial de Portugal neste setor, e ainda à grande dimensão do setor suinícola espanhol face ao português. Os resultados obtidos a partir da estimação de um modelo VAR(2), corroboram esta premissa, de que o preço do porco no mercado espanhol tem um grande impacto na formação do preço do porco no mercado nacional, sendo que as respostas a impulsos mostram que o efeito de choques nas inovações perduram durante um período extenso de tempo. Além disso, a partir do modelo VAR estimado, concluiu-se que o preço em Portugal também acaba por ter alguma influência sobre o preço do porco em Espanha, apesar de ter uma magnitude muito inferior quando comparado com o efeito inverso, dos preços em Espanha sobre os preços em Portugal. Os preços do trigo e do milho, principais cereais utilizados em alimentos compostos para suínos, não se revelaram estatisticamente significativos para explicar a formação do preço do porco, quer em Portugal, quer em Espanha, e apresentam baixos coeficientes de correlação contemporâneos e cruzados. Tais resultados, indiciam uma possível existência de assimetria na transmissão de preços, justificável com a dificuldade por parte dos produtores em repercutir nos preços dos seus outputs variações dos preços dos seus inputs. In Portugal, the behaviour of the pork producer price is mostly influenced by the trajectory of the pork producer price in Spain. Therefore one can consider that the Portuguese producers are price-takers against the Spanish pork market. This is caused by the closeness between these two countries and because Spain is the most important importer country of Portugal on this market. We also can't forget that Spain is the third country in the ranking of the biggest pork exporter countries in the world. The results of an estimated VAR model with order 2, prove that the producer price in the Spanish pork market has a great impact on the formation of the pork price in the Portuguese market. The responses to impulses show us that the effect of shocks in innovations persist for a long time. Furthermore, we have concluded that the Portuguese producer price of pork has an effect on the pork producer price in Spain, although this effect is relatively smaller than opposite situation. Based on available data, the price of wheat and corn in both Portugal and Spain, which is the principal components of pork's compound feed, aren't statistically significant to explain the pork price formation, and present a low coefficient of contemporary and cross correlation. These results show a possible situation of price transmission asymmetry which is justifiable considering the farmers' difficulties in passing the input prices variations to their output prices.

Avec les avancements de la technologie de l'information, les données temporelles économiques et financières sont de plus en plus disponibles. Par contre, si les techniques standard de l'analyse des séries temporelles sont utilisées, une grande quantité d'information est accompagnée du problème de dimensionnalité. Puisque la majorité des séries d'intérêt sont hautement corrélées, leur dimension peut être réduite en utilisant l'analyse factorielle. Cette technique est de plus en plus populaire en sciences économiques depuis les années 90. Étant donnée la disponibilité des données et des avancements computationnels, plusieurs nouvelles questions se posent. Quels sont les effets et la transmission des chocs structurels dans un environnement riche en données? Est-ce que l'information contenue dans un grand ensemble d'indicateurs économiques peut aider à mieux identifier les chocs de politique monétaire, à l'égard des problèmes rencontrés dans les applications utilisant des modèles standards? Peut-on identifier les chocs financiers et mesurer leurs effets sur l'économie réelle? Peut-on améliorer la méthode factorielle existante et y incorporer une autre technique de réduction de dimension comme l'analyse VARMA? Est-ce que cela produit de meilleures prévisions des grands agrégats macroéconomiques et aide au niveau de l'analyse par fonctions de réponse impulsionnelles? Finalement, est-ce qu'on peut appliquer l'analyse factorielle au niveau des paramètres aléatoires? Par exemple, est-ce qu'il existe seulement un petit nombre de sources de l'instabilité temporelle des coefficients dans les modèles macroéconomiques empiriques? Ma thèse, en utilisant l'analyse factorielle structurelle et la modélisation VARMA, répond à ces questions à travers cinq articles. Les deux premiers chapitres étudient les effets des chocs monétaire et financier dans un environnement riche en données. Le troisième article propose une nouvelle méthode en combinant les modèles à facteurs et VARMA. Cette approche est appliquée dans le quatrième article pour mesurer les effets des chocs de crédit au Canada. La contribution du dernier chapitre est d'imposer la structure à facteurs sur les paramètres variant dans le temps et de montrer qu'il existe un petit nombre de sources de cette instabilité. Le premier article analyse la transmission de la politique monétaire au Canada en utilisant le modèle vectoriel autorégressif augmenté par facteurs (FAVAR). Les études antérieures basées sur les modèles VAR ont trouvé plusieurs anomalies empiriques suite à un choc de la politique monétaire. Nous estimons le modèle FAVAR en utilisant un grand nombre de séries macroéconomiques mensuelles et trimestrielles. Nous trouvons que l'information contenue dans les facteurs est importante pour bien identifier la transmission de la politique monétaire et elle aide à corriger les anomalies empiriques standards. Finalement, le cadre d'analyse FAVAR permet d'obtenir les fonctions de réponse impulsionnelles pour tous les indicateurs dans l'ensemble de données, produisant ainsi l'analyse la plus complète à ce jour des effets de la politique monétaire au Canada. Motivée par la dernière crise économique, la recherche sur le rôle du secteur financier a repris de l'importance. Dans le deuxième article nous examinons les effets et la propagation des chocs de crédit sur l'économie réelle en utilisant un grand ensemble d'indicateurs économiques et financiers dans le cadre d'un modèle à facteurs structurel. Nous trouvons qu'un choc de crédit augmente immédiatement les diffusions de crédit (credit spreads), diminue la valeur des bons de Trésor et cause une récession. Ces chocs ont un effet important sur des mesures d'activité réelle, indices de prix, indicateurs avancés et financiers. Contrairement aux autres études, notre procédure d'identification du choc structurel ne requiert pas de restrictions temporelles entre facteurs financiers et macroéconomiques. De plus, elle donne une interprétation des facteurs sans restreindre l'estimation de ceux-ci. Dans le troisième article nous étudions la relation entre les représentations VARMA et factorielle des processus vectoriels stochastiques, et proposons une nouvelle classe de modèles VARMA augmentés par facteurs (FAVARMA). Notre point de départ est de constater qu'en général les séries multivariées et facteurs associés ne peuvent simultanément suivre un processus VAR d'ordre fini. Nous montrons que le processus dynamique des facteurs, extraits comme combinaison linéaire des variables observées, est en général un VARMA et non pas un VAR comme c'est supposé ailleurs dans la littérature. Deuxièmement, nous montrons que même si les facteurs suivent un VAR d'ordre fini, cela implique une représentation VARMA pour les séries observées. Alors, nous proposons le cadre d'analyse FAVARMA combinant ces deux méthodes de réduction du nombre de paramètres. Le modèle est appliqué dans deux exercices de prévision en utilisant des données américaines et canadiennes de Boivin, Giannoni et Stevanovic (2010, 2009) respectivement. Les résultats montrent que la partie VARMA aide à mieux prévoir les importants agrégats macroéconomiques relativement aux modèles standards. Finalement, nous estimons les effets de choc monétaire en utilisant les données et le schéma d'identification de Bernanke, Boivin et Eliasz (2005). Notre modèle FAVARMA(2,1) avec six facteurs donne les résultats cohérents et précis des effets et de la transmission monétaire aux États-Unis. Contrairement au modèle FAVAR employé dans l'étude ultérieure où 510 coefficients VAR devaient être estimés, nous produisons les résultats semblables avec seulement 84 paramètres du processus dynamique des facteurs. L'objectif du quatrième article est d'identifier et mesurer les effets des chocs de crédit au Canada dans un environnement riche en données et en utilisant le modèle FAVARMA structurel. Dans le cadre théorique de l'accélérateur financier développé par Bernanke, Gertler et Gilchrist (1999), nous approximons la prime de financement extérieur par les credit spreads. D'un côté, nous trouvons qu'une augmentation non-anticipée de la prime de financement extérieur aux États-Unis génère une récession significative et persistante au Canada, accompagnée d'une hausse immédiate des credit spreads et taux d'intérêt canadiens. La composante commune semble capturer les dimensions importantes des fluctuations cycliques de l'économie canadienne. L'analyse par décomposition de la variance révèle que ce choc de crédit a un effet important sur différents secteurs d'activité réelle, indices de prix, indicateurs avancés et credit spreads. De l'autre côté, une hausse inattendue de la prime canadienne de financement extérieur ne cause pas d'effet significatif au Canada. Nous montrons que les effets des chocs de crédit au Canada sont essentiellement causés par les conditions globales, approximées ici par le marché américain. Finalement, étant donnée la procédure d'identification des chocs structurels, nous trouvons des facteurs interprétables économiquement. Le comportement des agents et de l'environnement économiques peut varier à travers le temps (ex. changements de stratégies de la politique monétaire, volatilité de chocs) induisant de l'instabilité des paramètres dans les modèles en forme réduite. Les modèles à paramètres variant dans le temps (TVP) standards supposent traditionnellement les processus stochastiques indépendants pour tous les TVPs. Dans cet article nous montrons que le nombre de sources de variabilité temporelle des coefficients est probablement très petit, et nous produisons la première évidence empirique connue dans les modèles macroéconomiques empiriques. L'approche Factor-TVP, proposée dans Stevanovic (2010), est appliquée dans le cadre d'un modèle VAR standard avec coefficients aléatoires (TVP-VAR). Nous trouvons qu'un seul facteur explique la majorité de la variabilité des coefficients VAR, tandis que les paramètres de la volatilité des chocs varient d'une façon indépendante. Le facteur commun est positivement corrélé avec le taux de chômage. La même analyse est faite avec les données incluant la récente crise financière. La procédure suggère maintenant deux facteurs et le comportement des coefficients présente un changement important depuis 2007. Finalement, la méthode est appliquée à un modèle TVP-FAVAR. Nous trouvons que seulement 5 facteurs dynamiques gouvernent l'instabilité temporelle dans presque 700 coefficients., As information technology improves, the availability of economic and finance time series grows in terms of both time and cross-section sizes. However, a large amount of information can lead to the curse of dimensionality problem when standard time series tools are used. Since most of these series are highly correlated, at least within some categories, their co-variability pattern and informational content can be approximated by a smaller number of (constructed) variables. A popular way to address this issue is the factor analysis. This framework has received a lot of attention since late 90's and is known today as the large dimensional approximate factor analysis. Given the availability of data and computational improvements, a number of empirical and theoretical questions arises. What are the effects and transmission of structural shocks in a data-rich environment? Does the information from a large number of economic indicators help in properly identifying the monetary policy shocks with respect to a number of empirical puzzles found using traditional small-scale models? Motivated by the recent financial turmoil, can we identify the financial market shocks and measure their effect on real economy? Can we improve the existing method and incorporate another reduction dimension approach such as the VARMA modeling? Does it help in forecasting macroeconomic aggregates and impulse response analysis? Finally, can we apply the same factor analysis reasoning to the time varying parameters? Is there only a small number of common sources of time instability in the coefficients of empirical macroeconomic models? This thesis concentrates on the structural factor analysis and VARMA modeling and answers these questions through five articles. The first two articles study the effects of monetary policy and credit shocks in a data-rich environment. The third article proposes a new framework that combines the factor analysis and VARMA modeling, while the fourth article applies this method to measure the effects of credit shocks in Canada. The contribution of the final chapter is to impose the factor structure on the time varying parameters in popular macroeconomic models, and show that there are few sources of this time instability. The first article analyzes the monetary transmission mechanism in Canada using a factor-augmented vector autoregression (FAVAR) model. For small open economies like Canada, uncovering the transmission mechanism of monetary policy using VARs has proven to be an especially challenging task. Such studies on Canadian data have often documented the presence of anomalies such as a price, exchange rate, delayed overshooting and uncovered interest rate parity puzzles. We estimate a FAVAR model using large sets of monthly and quarterly macroeconomic time series. We find that the information summarized by the factors is important to properly identify the monetary transmission mechanism and contributes to mitigate the puzzles mentioned above, suggesting that more information does help. Finally, the FAVAR framework allows us to check impulse responses for all series in the informational data set, and thus provides the most comprehensive picture to date of the effect of Canadian monetary policy. As the recent financial crisis and the ensuing global economic have illustrated, the financial sector plays an important role in generating and propagating shocks to the real economy. Financial variables thus contain information that can predict future economic conditions. In this paper we examine the dynamic effects and the propagation of credit shocks using a large data set of U.S. economic and financial indicators in a structural factor model. Identified credit shocks, interpreted as unexpected deteriorations of the credit market conditions, immediately increase credit spreads, decrease rates on Treasury securities and cause large and persistent downturns in the activity of many economic sectors. Such shocks are found to have important effects on real activity measures, aggregate prices, leading indicators and credit spreads. In contrast to other recent papers, our structural shock identification procedure does not require any timing restrictions between the financial and macroeconomic factors, and yields an interpretation of the estimated factors without relying on a constructed measure of credit market conditions from a large set of individual bond prices and financial series. In third article, we study the relationship between VARMA and factor representations of a vector stochastic process, and propose a new class of factor-augmented VARMA (FAVARMA) models. We start by observing that in general multivariate series and associated factors do not both follow a finite order VAR process. Indeed, we show that when the factors are obtained as linear combinations of observable series, their dynamic process is generally a VARMA and not a finite-order VAR as usually assumed in the literature. Second, we show that even if the factors follow a finite-order VAR process, this implies a VARMA representation for the observable series. As result, we propose the FAVARMA framework that combines two parsimonious methods to represent the dynamic interactions between a large number of time series: factor analysis and VARMA modeling. We apply our approach in two pseudo-out-of-sample forecasting exercises using large U.S. and Canadian monthly panels taken from Boivin, Giannoni and Stevanovic (2010, 2009) respectively. The results show that VARMA factors help in predicting several key macroeconomic aggregates relative to standard factor forecasting models. Finally, we estimate the effect of monetary policy using the data and the identification scheme as in Bernanke, Boivin and Eliasz (2005). We find that impulse responses from a parsimonious 6-factor FAVARMA(2,1) model give an accurate and comprehensive picture of the effect and the transmission of monetary policy in U.S.. To get similar responses from a standard FAVAR model, Akaike information criterion estimates the lag order of 14. Hence, only 84 coefficients governing the factors dynamics need to be estimated in the FAVARMA framework, compared to FAVAR model with 510 VAR parameters. In fourth article we are interested in identifying and measuring the effects of credit shocks in Canada in a data-rich environment. In order to incorporate information from a large number of economic and financial indicators, we use the structural factor-augmented VARMA model. In the theoretical framework of the financial accelerator, we approximate the external finance premium by credit spreads. On one hand, we find that an unanticipated increase in US external finance premium generates a significant and persistent economic slowdown in Canada; the Canadian external finance premium rises immediately while interest rates and credit measures decline. From the variance decomposition analysis, we observe that the credit shock has an important effect on several real activity measures, price indicators, leading indicators, and credit spreads. On the other hand, an unexpected increase in Canadian external finance premium shows no significant effect in Canada. Indeed, our results suggest that the effects of credit shocks in Canada are essentially caused by the unexpected changes in foreign credit market conditions. Finally, given the identification procedure, we find that our structural factors do have an economic interpretation. The behavior of economic agents and environment may vary over time (monetary policy strategy shifts, stochastic volatility) implying parameters' instability in reduced-form models. Standard time varying parameter (TVP) models usually assume independent stochastic processes for all TVPs. In the final article, I show that the number of underlying sources of parameters' time variation is likely to be small, and provide empirical evidence on factor structure among TVPs of popular macroeconomic models. To test for the presence of, and estimate low dimension sources of time variation in parameters, I apply the factor time varying parameter (Factor-TVP) model, proposed by Stevanovic (2010), to a standard monetary TVP-VAR model. I find that one factor explains most of the variability in VAR coefficients, while the stochastic volatility parameters vary in the idiosyncratic way. The common factor is highly and positively correlated to the unemployment rate. To incorporate the recent financial crisis, the same exercise is conducted with data updated to 2010Q3. The VAR parameters present an important change after 2007, and the procedure suggests two factors. When applied to a large-dimensional structural factor model, I find that four dynamic factors govern the time instability in almost 700 coefficients.

The classified pricing of fluid milk under the Federal Milk Marketing Orders (FMMO) system combined with the cash settlement feature of Class IIII milk futures contracts generate a unique volatility pattern of these futures markets in the sense that the volatility gradually decreases as the USDA price announcement dates approaching in the month. Focusing on the evolution of volatility in Class III milk futures market, this study quantifies the relative importance of a set of factors driving milk price variation. While volatilities in both corn futures market and financial market Granger-cause the milk price volatility, the impact of financial market is more persistent. Besides embedded seasonality, market demand and supply conditions in the dairy market, cheese in this case, as well as changes in the U.S. exchange rates are found to have positive and statistically significant impacts on milk price volatility. While speculation positively affects milk futures markets, the effect was found insignificant.

This paper considers the problem of aggregation in the case of large linear dynamic panels, where each micro unit is potentially related to all other micro units, and where micro innovations are allowed to be cross sectionally dependent. Following Pesaran (2003), an optimal aggregate function is derived, and the limiting behavior of the aggregation error is investigated as N (the number of cross section units) increases. Certain distributional features of micro parameters are also identified from the aggregate function. The paper then establishes Granger's (1980) conjecture regarding the long memory properties of aggregate variables from .a very large scale dynamic, econometric model., and considers the time profiles of the effects of macro and micro shocks on the aggregate and disaggregate variables. Some of these findings are illustrated in Monte Carlo experiments, where we also study the estimation of the aggregate effects of micro and macro shocks. The paper concludes with an empirical application to consumer price inflation in Germany, France and Italy, and re-examines the extent to which 'observed' inflation persistence at the aggregate level is due to aggregation and/or common unobserved factors. Our findings suggest that dynamic heterogeneity as well as persistent common factors are needed for explaining the observed persistence of the aggregate inflation.

Erzincan ili nüfusu il merkezinde 94.000 olup trafiğe kayıtlı araç sayısı ise 30.000’dir. Bu rakamlar kişi başına yaklaşık 3 araç düştüğünü göstermektedir. İl merkezinin Kuzey Transit Karayolu üzerinde olması da Türkiye için stratejik bir öneme sahip olmasını sağlamıştır. Yıllık ortalama günlük trafik (YOGT) değeri D-100 (E-80) karayolunda 5125 araçtır. Bu konuma binaen Erzincan ilinde meydana gelen trafik kazaları ve bunların nüfus ve araç sayısı ile olan ilişkileri önemli olarak görülmüştür. Ülkemizde insan ölümleri nedenleri içinde trafik kazaları üçüncü sırayı almaktadır. 1. 200.000 araç bir yılda ölümlü, yaralanmalı ve maddi hasarlı trafik kazasına karışmaktadır. Bütün bu korkunç bilanço karşısında trafik kazalarına sebep veren değişkenleri incelemek, bunların farklı istatistik metotlarla analizini yapmak bu çalışmanın hedefleri arasındadır. William et al. (1973) yaptıkları bir çalışmada, tek başına kaza sayılarını alıp kaza analizinden ziyade Bayesci bir yaklaşım ile bir kesitteki kaza potansiyelinin analiz edilmesi gerektiğini önermişlerdir. İyinam vd (1998), tek değişkenli zaman serisi analizi ile aylık trafik kaza sayılarını modelleyip, kaza sayılarının 20 yıllık bir süreçte ne ölçüde arttığını gözlemlemişlerdir. Camkesen (1998), trafik kazalarının oluşumunda birden fazla faktörün rol aldığını ifade etmektedir. Bu faktörlerin tamamının birbirleri ile olan ilişkileri, yolların geometrik özellikleri, çevre koşulları ve sürücü karakteristikleri kazaların oluşumunda büyük rol oynamaktadırlar. Delen vd (2003), Yapay Sinir Ağları (YSA) yardımıyla sürücü karakteristiklerinin çevresel faktörlerin ve yol şartlarının kaza anındaki rolünü modellemeye çalışmıştır. Ozgan (2008) çalışmasında, karayolunda kullanılan araç tipleri ile kaza sonuçları arasındaki ilişkiyi lineer regresyon modeli ile ifade etmiştir. Türe (2008) çalışmasında, poisson ve negatif binomial (NB) regresyon yöntemlerinin kaza analizinde daha çok kullanıldığını belirtmiştir. Trabzon bölünmüş karayolunda yapmış olduğu çalışmada hız ve kavşak sayısının kaza sayısını azaltıcı bir rol oynadığını tespit etmiştir. Nakatsyii (1989) ve Altun vd (2005) yapay sinir ağları yardımıyla trafik akım kontrolü isimli bir çalışma yapmışlardır. Bu çalışmada sürücülerin karakteristik özellikleri (yaş, cinsiyet, alkol durumu, emniyet kemeri), araç tipi, hız, bölge özellikleri, aydınlık durumu gibi değişkenler girdi katmanında yer almıştır. Çıkış katmanında ise kazanın hasarsız, hafif hasarlı, orta şiddetli, ağır ve ölümcül olup olmadıkları yapay sinir ağları, fuzzy (bulanık mantık), probit model ile modellenmeye çalışılmış ve yöntemler kıyaslanmıştır. Aynı çalışmada trafik akımı ve hızı tahmin edilmeye çalışılmıştır. Yoğunluk, hava durumu, görüş, açıklık ve ağır taşıt yüzdesi değişkenleri alınmış, 360.000 trafik kaydının içinden 2688 âdeti seçilmiş, verilerin yarısı ağın eğitimi yarısı da ağın testi için kullanılmıştır. Bayata ve Hattatoğlu (2010) çalışmasında 1974–2007 yılları arasındaki ceza alan sürücü sayıları ile kaza sayıları dikkate alınarak, çok değişkenli istatistiksel analiz (ÇDR) ve yapay sinir ağları (YSA) yöntemleri ile modelleme yapılmıştır. Ceza alan sürücülerin sayısının artmasının, kaza sayılarında bir azalma göstermediği tespit edilmiştir. İstatistiksel değerlendirmelerinde, YSA’nın ÇDR’ye göre daha yüksek bir R2 değeri olduğu ve ortalama karesel hatasının da (OKH) minimum olduğu bulunmuştur. Sonuçta YSA yönteminin istatistiksel olarak daha başarılı bir yöntem olduğu ifade edilmiştir. Bu çalışmada iki farklı istatistik yöntem kullanılarak, sonuçlar itibariyle yöntemler birbirleri arasında karşılaştırılmıştır. Yapay sinir ağları (YSA) yöntemi çok değişkenli zaman serisi yöntemine göre istatistiksel olarak daha başarılı bulunmuştur. Kaza sayılarını etkileyen bağımsız değişkenlerden olan nüfus ve araç sayısındaki artışın, kaza sayılarında artışa sebep olduğu görülmüştür., Bu çalışmada, Erzincan ilinde 1985-2010 yılları arasında meydana gelen yıllık trafik kaza sayıları kullanılarak farklı istatistiksel yöntemlerle modelleme yapılmıştır. Modellerde trafik kaza sayıları bağımlı değişken olarak kabul edilmiştir. Aynı yılları kapsayan nüfus, araç sayısı, ölü sayısı ve yaralı sayıları ise bağımsız değişken olarak kabul edilmiştir. Bu veriler yapay sinir ağları (YSA) ve çok değişkenli zaman serileri yöntemleri ile modellenmiştir. YSA yönteminde trafik kazaları değerleri [0, 1] arasında bir ölçeklemeye tabii tutulmuştur. Zaman serisi analizi ile seri durağan hale getirilmiştir. Etki tepki analizi ve varyans ayrıştırması yapılarak nüfus ve araç sayısındaki bir birimlik şokların kaza sayısı üzerindeki etkileri araştırılmıştır. Kaza sayılarını etkileyen değişkenler arasında, araç sayısı nüfusa göre istatistiksel olarak daha anlamlı çıkmıştır. Yöntemler kıyaslanırken ortalama karesel hata (OKH), belirlilik katsayısı (R2) ve Akaike bilgi kriterine (AIC) göre en iyi model belirlenmiştir. Yöntemler arasında YSA yönteminin R2 değeri diğer yönteme göre daha yüksek, ortalama karesel hatası (OKH) ise daha düşük çıkmıştır. Bu sonuçlara göre YSA yönteminin istatistiksel olarak daha başarılı olduğu görülmüştür. In this study, models were established with different statistical methods by using traffic accidents number occurred in Erzincan city between 1985-2010 years. In these models, traffic accidents number was taken as dependent variable. Populations, the number of vehicle, dead and injured were taken as independent variables. These data were modeled by Artificial Neural Networks and Multivariate time series analyses methods. Traffic accidents numbers values were scaled between [0,1]. Series were rearranged as stable by time series analyses. It was investigated that a unit shocks on population and vehicle numbers effected traffic accident numbers by impulse responses and variance decomposition Statistically, the number of vehicles was more significant than population. Mean squared error (MSE), Coefficient of Determination (R2) and Akaike Information Criteria (AIC) were used for comparing the methods. Since ANN method has higher R2 and lower MSE, it was seen that ANN method was more successfully than other.

This paper explores the behavior of profits in the four largest euro area countries (Germany, France, Italy and Spain) and the euro area as a whole, while at the same time considering three main sectors (manufacturing, construction and services) in each economy over the period 1988–2010. The paper presents stylized facts about profit developments and, applying a vector autoregressive modeling framework, discusses the sensitivity of profits to four distinctive structural shocks (a demand shock, an employment shock, a wage and price mark-up shocks). In addition, it provides the shock decomposition of historical developments in profits across countries and sectors.

This paper contributes to the literature on the changing transmission mechanism of monetary policy by introducing a model whose parameter evolution explicitly depends on the conduct of monetary policy. We find that the model fits the data well, in particular when complemented with an estimated break around 1985 that could be associated with the re-gained credibility of the central bank. The responses of output and inflation to policy shocks change not only because of the break in 1985 but also according to the monetary policy stance: policy shocks have stronger negative effects when policy is tight. There is also evidence in favour of large changes in the volatility of the output equation, but not of inflation. A set of counterfactual experiments indicate that good policy and good luck contributed to the "great moderation", but neither of them can fully explain it. A more general variation in the model dynamics underlying the shock transmission mechanism is required.

The acoustic impulse responses of a family of nonuniform lossless one-dimensional media are determined. The nonuniform portions of the media are confined to layers of either finite or infinite thicknesses. The acoustic impedances of the nonuniform layers as functions of travel time are assumed known. The impulse responses are determined by evaluating the Fourier transforms of their reflection coefficients using infinite series expansions and contour integrations.

This paper studies the transmission of shocks and the trade-offs between stabilizing CPI inflation and alternative measures of the output gap in Ramses, the Riksbank’s empirical dynamic stochastic general equilibrium (DSGE) model of a small open economy. The main results are, first, that the transmission of shocks depends substantially on the conduct of monetary policy, and second, that the trade-off between stabilizing CPI inflation and the output gap strongly depends on which concept of potential output in the output gap between output and potential output is used in the loss function. If potential output is defined as a smooth trend this trade-off is much more pronounced compared to the case when potential output is defined as the output level that would prevail if prices and wages were flexible.

This paper studies the transmission of shocks and the trade-offs between stabilizing CPI inflation and alternative measures of the output gap in Ramses, the Riksbank's empirical dynamic stochastic general equilibrium (DSGE) model of a small open economy. The main results are, first, that the transmission of shocks depends substantially on the conduct of monetary policy, and second, that the trade-off between stabilizing CPI inflation and the output gap strongly depends on which concept of potential output in the output gap between output and potential output is used in the loss function. If potential output is defined as a smooth trend this trade-off is much more pronounced compared to the case when potential output is defined as the output level that would prevail if prices and wages were flexible.

Mestrado em Economia. O investimento público tem sido alvo de interesse por parte das investigações económicas mais recentes, enquanto uma variável que pode fomentar o crescimento económico. Através da observação dos seus impactos na economia, consegue-se compreender se os esforços empreendidos no investimento público são eventualmente produtivos. Este estudo pretende analisar essa produtividade, medindo os efeitos do investimento público no PIB, no investimento privado e no emprego, no longo prazo. A especificidade do exposto neste trabalho consiste numa desagregação diferente do investimento público, ao analisar em separado os efeitos do investimento feito pela administração central, pela administração local e pela administração estadual, quando aplicável. É efectuado para sete países da União Europeia, a saber; Alemanha, Bélgica, Finlândia, França, Holanda, Itália e Portugal, permitindo assim uma comparação a nível internacional. A abordagem metodológica baseia-se em modelos de vectores autoregressivos - modelos VAR. Com base nas funções acumuladas de resposta a um impulso por tipo de investimento público, são calculadas as elasticidades, as produtividades marginais parciais e totais do PIB e do investimento privado, bem como as taxas de rendibilidade parciais e totais do PIB. É ainda calculado o número marginal de empregos criados. Conclui-se que, de modo geral, o investimento público por subsector é produtivo, apresentando efeitos positivos no PIB, no investimento privado e no emprego. Por tipo de investimento público, o investimento local tem sempre efeitos positivos no PIB, apresenta impactos positivos no investimento privado para um maior número de países e, no emprego, embora as elasticidades de longo prazo sejam superiores, os empregos criados são menores do que para o investimento central. Public investment has been a target of many economical investigations in the recent years, because of its potential to promote economic growth. Through the observation of its impacts in the economy, one can understand if the efforts of public investment are productive. The aim of this study is to analyse that productivity, through the measurement of the public investment effects in the long run in GDP, private investment and employment. The specificity of this work, is the different disaggregation of public investment, that analyse separately the effects of public investment made by the central administration, local administration and state administration, when exists. It is made to seven European Union countries: Germany, Belgium, Finland, France, Netheriands, Italy and Portugal, allowing an intemational comparison. The methodological approach is a model of vector autoregression - a VAR model. With theaccumulated impulse response functions for different t ypes of public investment, elasticities, partial and total marginal productivities and, partial and total rates of retum are calculated for GDP. The number of marginal jobs is also calculated. One can conclude that, generally, public investment is productive, with positive effects in GDP, in private investment and in employment. For a analyse through different types of public investment, the local one hasalways positive effects in GDP, has positive effects in private investment for most countries and, in employment, although the elasticities are greater, the job creation are less than for the central investment. info:eu-repo/semantics/publishedVersion

As Italy possesses a rich heritage of Opera houses and since, owing to the period in which they were built, they were not planned for electroacoustical amplification systems and the quality of the listening conditions in the theatres was still wholly due to their spatial characteristics, the materials and the techniques used to build them, the Teatro Comunale of Bologna was chosen for this research. An experimental measuring campaign was conducted in this late 18th century “Italian-style” theatre so as to define a map of the impulse responses (IR) able to significantly represent the acoustics perceived by the audience seated in the stalls or balconies. Using the geometric and constructional data, a three-dimensional model of the theatre was then made and used to numerically simulate the acoustic properties in the theatre and, after appropriate calibration, the respective impulse responses were calculated in the same points as where the measurements had been taken in the experimental campaign. Lastly, the method for auralising an anechoic signal was used for qualitatively comparing the simulation of the theatre’s acoustic response. This was done by calculating an IR from the experimental data and extrapolating an IR from the numeric model.

The virtual reconstruction of sound properties of musical instruments could be obtained starting from the measurements of impulse responses of the sound chests of violins and violas or the bore of trumpets and flutes. Convolving the sound signals of the player captured just after his performance and before the body of the instruments, the final effect of the musician can be reconstructed. However only the linear components of the body could be reproduced, whereas all not linearity is not taken into account. In this paper a novel technique for measuring and reproducing not-linear sound characteristics of musical instruments is presented. The method has been applied to capture both acoustic (pressure) and vibration (body’s particle velocity) impulse responses. The new method, starting from Volterra Kernel expression of not-linearity, has been applied to few wind instruments up to 5th order of distortion. The intensity of acoustic radiation has been measured and the influence of not-linearity has been evaluated in sound reconstruction and compared with previous methods.

We empirically analyse the response of US manufacturing labour market variables to various shocks, notably to trade openness and technology. The econometric approach involves an application of the recently developed global VAR (GVAR) methodology of D¶ees, DiMauro, Pesaran, and Smith (2005) to 12 manufacturing industries over the period 1977-2003. This frame-work allows for an assessment of both shocks to weakly exogenous variables and intra-industry spillovers. In this vein, beyond a standard set of labour-market related variables (employment, real compensation, productivity and capital stock) and exogenous factors (a sector-specific measure of trade openness, along with common technology and oil price shocks), specific measures of manufacturing-wide variables are included for each sector. Generalised impulse responses indicate that increased trade openness negatively affects real compensation, has negligible employment effects and leads to higher labour productivity. These impacts, however, are relatively weaker those induced by technology shocks, with the latter positively and significantly affecting both real compensation and employment. There is also evidence of positive spill-overs across industries from sector-specific employment and productivity shocks. Impact elasticities suggest strong intra-sectoral linkages for employment and capital stock formation, contrasting with weak linkages for what concerns real compensation and productivity.

Croatia is on its path to the EU. Developments on this path have influence on many aspects in the economy. In this paper we analyse integration of Croatian equity market with European and world equity markets and measure integration with the VAR impulse responses and variance decomposition. The premise is that well integrated markets should respond to shocks similarly. According to this test, major world markets (measured by DJIA, FTSE and DAX) indeed display certain degree of shock transmission. Opposite, Croatian and other less important markets in CEE economies that were tested do not show the same degree of integration. It seems that in terms of transfer of short term shocks between markets, Croatia and other CEE economies are still pretty much isolated from the world.

The implied volatility of a European option as a function of strike price and time to maturity forms a volatility surface. Traders price according to the dynamics of this high dimensional surface. Recent developments that employ semiparametric modelsapproximate the implied volatility surface (IVS) in a finite dimensional function space,allowing for a low dimensional factor representation of these dynamics. This paperpresents an investigation into the stochastic properties of the factor loading times seriesusing the vector autoregressive (VAR) framework and analyzes associated movements of these factors with movements in some macroeconomic variables of the Euro-economy.

This paper estimates the effects of technology shocks in VAR models of the U.S., identified by imposing restrictions on the sign of impulse responses. These restrictions are consistent with the implications of a popular class of DSGE models, with both real and nominal frictions, and with sufficiently wide ranges for their parameterers. This identification strategy thus substitutes theoretically-motivated restrictions for the atheoretical assumptions on the time-series properties of the data that are key to long-run restrictions. Stochastic technology improvements persistently increase real wages, consumption, investment and output in the data; hours worked are very likely to increase, displaying a hump-shaped pattern. Contrary to most of the related VAR evidence, results are not sensitive to a number of specification assumptions, including those on the stationarity properties of variables. JEL Classification: C3, E3

In structural vector autoregressive (SVAR) models identifying restrictions for shocks and impulse responses are usually derived from economic theory or institutional constraints. Sometimes the restrictions are insufficient for identifying all shocks and impulse responses. In this paper it is pointed out that specific distributional assumptions can also help in identifying the structural shocks. In particular, a mixture of normal distributions is considered as a plausible model that can be used in this context. Our model setup makes it possible to test restrictions which are just-identifying in a standard SVAR framework. In particular, we can test for the number of transitory and permanent shocks in a cointegrated SVAR model. The results are illustrated using a data set from King, Plosser, Stock and Watson (1991) and a system of US and European interest rates.

This paper assesses the effect of monetary policy on major components of aggregate demand. We use three different macromodels, all estimated on Hungarian data of the past 10 years. All three models indicated that after an unexpected monetary policy tightening investments decrease quickly. The response of consumption is more ambiguous, but it is most likely to increase for several years, which may be explained by the slow adjustment of nominal wages. On the other hand, we could not detect any significant change in net exports during the first couple of years after the shock. The weak response of net exports can be due to the fact that the drop in exports is coupled with a fall in imports of almost the same magnitude, highlighting the relative importance of the income-absorption effect, as opposed to the expenditure-switching effect.

We explore the international spillovers from fiscal policy shocks via trade in Europe. A fiscal expansion stimulates domestic activity, which leads to more foreign exports and, hence, higher foreign output. To quantify this, we combine a panel VAR model in government spending, net taxes and GDP with a panel trade model. On average, a public spending increase equal to 1% of GDP implies 2.3% more foreign exports over the first two years. The corresponding figure for an equal-size net tax reduction is 0.6%. Both estimates are statistically significant. As far as the effect on foreign activity is concerned, a 1% of GDP spending increase (net tax reduction) in Germany on average raises GDP of trading partners by 0.23% (0.06%) over the first two years. These figures are likely to form lower bounds for the actual effects and suggest that it may be worthwhile to further investigate the benefits from coordinated fiscal expansions (contractions) in response to European-wide cyclical downturns (upswings).

We investigate identifiability issues in DSGE models and their consequences for parameter estimation and model evaluation when the objective function measures the distance between estimated and model impulse responses. We show that observational equivalence, partial and weak identification problems are widespread, that they lead to biased estimates, unreliable t-statistics and may induce investigators to select false models. We examine whether different objective functions affect identification and study how small samples interact with parameters and shock identification. We provide diagnostics and tests to detect identification failures and apply them to a state-of-the-art model.

This paper presents a global model linking individual country vector error-correcting models in which the domestic variables are related to the country-specific variables as an approximate solution to a global common factor model. This global VAR is estimated for 26 countries, the euro area being treated as a single economy. This paper proposes two important extensions of previous research (see Pesaran, Schuermann and Weiner, 2004). First, it provides a theoretical framework where the GVAR is derived as an approximation to a global unobserved common factor model. Also using average pair-wise cross-section error correlations, the GVAR approach is shown to be quite effective in dealing with the common factor interdependencies and international comovements of business cycles. Second, in addition to generalised impulse response functions, we propose an identification scheme to derive structural impulse responses. We focus on identification of shocks to the US economy, particularly the monetary policy shocks, and consider the time profiles of their effects on the euro area. To this end we include the US model as the first country model and consider alternative orderings of the US variables. Further to the US monetary policy shock, we also consider oil price, US equity and US real output shocks.

We use a Vector Auto Regression (VAR) analysis to explore the (spill-over) effects of fiscal policy shocks in Europe. To enhance comparability with the existing literature, we first analyse the effects of these shocks at the national level. Here, we employ identification based on Choleski decomposition and a structural VAR, both of which lead to the same results. Then, we turn to study the cross-border spill-overs of fiscal shocks via the trade channel. Fiscal expansions in Germany, France and Italy lead to significant increases in imports from a number of European countries. In order to mimic the case of monetary union, we also shut off the effects via the short-term interest rate and the nominal exchange rate and find a slight strengthening on average of the cross-country spill-overs from a fiscal expansion. These results suggest that it may be worthwhile to further investigate the possibility of enhanced fiscal coordination.

Structural VARs have been extensively used in empirical macroeconomics during the last two decades, particularly in analyses of monetary policy. Existing Bayesian procedures for structural VARs are at best confined to a severly limited handling of cointegration restrictions. This paper extends the Bayesian analysis of structural VARs to cover cointegrated processes with an arbitrary number of cointegrating relations and general linear restrictions on the cointegration space. A reference prior distribution with an optional small open economy effect is proposed and a Gibbs sampler is derived for a straightforward evaluation of the posterior distribution. The methods are used to analyze the effects of monetary policy in Sweden. JEL Classification: C11, C32, E52

Housing systems, as a major sector of industrialised economies, might have profound effects on the transmission mechanism of a monetary shock. Despite a progressive convergence, however, EU countries still differ significantly in their housing and credit market institutions. This paper provides a theoretical discussion of the "housing market" channels of the monetary transmission mechanism (MTM) and offers some evidence on institutional differences across EU countries. Using recursive and semi-structural VARs, we identify monetary policy shocks and assess their effects on residential prices in eight European countries over the EMS period. Results show a different degree of sensitivity of house prices, partly consistent with the institutional features of the European housing systems. We then investigate the importance of these policy-induced changes in house prices in transmitting monetary shocks to the private consumption. In some countries, results provide some support for the view that house price channel may be an important source of MTM to consumption.

An important preliminary step in impulse response analysis is to select the vector autoregressive (VAR) lag order from the data, yet little is known about the implications of alternative lag order selection criteria for the accuracy of the impulse response estimates. In this Paper, we compare the criteria most commonly used in applied work in terms of the mean-squared error of the implied impulse response estimates. We conclude that for monthly VAR models, the Akaike Information Criterion (AIC) produces the most accurate structural and semi-structural impulse response estimates for realistic sample sizes. For quarterly VAR models, the Hannan-Quinn Criterion (HQC) appears to be the most accurate criterion with the exception of sample sizes smaller than 120, for which the Schwarz Information Criterion (SIC) is more accurate. For persistence profiles based on quarterly vector error correction (VEC) models, the SIC is the most accurate criterion for all realistic sample sizes. Sequential Lagrange-multiplier and likelihood ratio tests cannot be recommended.

This paper examines sources of cyclical movements in output, inflation and the term structure of interest rates. It employs a novel identification approach which uses the sign of the cross correlation function in response to shocks to catalog orthogonal disturbances. We find that demand shocks are the dominant source output, inflation and term structure fluctuations in six of the G-7 countries. Within the class of demand disturbances, nominal shocks are dominant, but their importance declined after 1982. Furthermore, there are no significant differences in the proportion of term structure variability explained by different structural sources at different horizons.

An introduction to vector autoregressive (VAR) analysis is given with special emphasis on cointegration. The models, estimating their parameters and specifying the autoregressive order, the cointegrating rank and other restrictions are discussed. Possibilities for model validation are also considered, Causality tests, impulse responses and forecast error variance decompositions are presented as tools for analyzing VAR models.

Following standard real business cycle theory, long run economic growth and short run business cycle fluctuations are attributed to a series of productivity shocks propagated by the economic system which is assumed to be in a rational expectations equilibrium. Characterizing the technical progress as the common stochastic trend we are able to investigate the short and long run effects of the productivity shocks using a cointegrated system. From the empirical analysis it emerges that the long run relationship between the system variables can be traced back to a single permanent component which is interpreted as a measure of technological progress. The short run dynamic impact of the permanent innovations is investigated using the empirical impulse response functions. It turns out that the permanent shocks are able to explain a substantial portion of business cycle fluctuations.

This paper proposes a systematic framework for analyzing the dynamic effects of permanent and transitory shocks on a system of n economic variables. We consider a two-step orthogonolization on the residuals of a VECM with r cointegrating vectors. The first step separates the permanent from the transitory shocks, and the second step isolates n?r mutually uncorrelated permanent shocks and r transitory shocks. The decomposition is computationally straightforward and entails only a minor modification to the Choleski decomposition commonly used in the literature. We then show how impulse response functions can be constructed to trace out the propagating mechanism of shocks distinguished by their degree of persistence. In an empirical example, the dynamic responses to the identified permanent shocks have properties similar to shocks to productivity, the real interest rate, and money growth, even though no economic theory was used to achieve the identification. We highlight two numerical issues that could affect any identification of permanent and transitory shocks. Publicado

This study examines the long-run neutrality of money and the short-run dynamics of farm and nonfarm prices to the monetary shock, using Johansen'Â’s approach. Results find a long-run equality of prices, but not neutrality. In the short-run, farm prices adjust faster than nonfarm prices to a monetary shock.

The Fisherian hypothesis was tested for four regional agricultural interest rates in the 11th Federal Reserve District (Dallas). These interest rates represented agricultural loans of different terms to maturity. Shocks in expected inflation resulted in positive but less than equivalent responses in all four rates. The empirical evidence from the impulse response function suggested that Fisher's relationship holds imperfectly for agricultural interest rates in the Dallas Federal Reserve District.

With a panel VAR of 10 Euro area countries we study the budgetary determinants of government bond yield spreads vis-à-vis Germany between 1999Q1 and 2012Q4. We find that rising bid ask, VIX and debt differentials increase yield spreads; and improvements in the budget balance, higher growth prospects and depreciation lower the spreads. Moreover, rises in public wages or in social expenditure increase spreads, while increases in direct and indirect taxes lower the yield spreads. In the post-2007Q3 crisis period, rising expenditure components (except subsidies) increased spreads.

The article has experimented with a methodology for using vector autoregressive models (VAR) to study the impact of shocks in the business climate and economic activity on the business cycles of final consumption expenditure of households. It refers to six countries in Central and Eastern Europe (Bulgaria, Czech Republic, Hungary, Poland, Romania and Slovakia) for the period 2000 to 2015. The results show that the expectations for the financial situation of households over the next 12 months and the level of employment have a stimulating effect on the business cycle of final consumption expenditure of households. The expectations for unemployment,inflation and savings over the next 12 months have a negative impact on the business cycles.

This paper investigates which shocks drive asynchrony of business cycles in the euro area. Thereby, it unites two strands of literature, those on common features and on structural VAR analysis. In particular, we show that the presence of a common cycle implies collinearity of structural impulse responses. Several Wald tests are applied to the latter hypothesis. Results reveal that differences in the GDP dynamics in several peripheral countries compared to a euro zone core are triggered by idiosyncratic, and to a lesser extent also world, shocks. Additionally, real shocks prove relevant rather than nominal ones.